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Earth Observation

Earth Observation (EO) refers to the use of remote sensing technologies to monitor land, marine (seas, rivers, lakes) and atmosphere. Satellite-based EO relies on the use of satellite-mounted payloads to gather imaging data about the Earth’s characteristics. The images are then processed and analyzed in order to extract different types of information that can serve a very wide range of applications and industries.

Papers

Showing 125 of 518 papers

TitleStatusHype
PyramidMamba: Rethinking Pyramid Feature Fusion with Selective Space State Model for Semantic Segmentation of Remote Sensing ImageryCode5
TerraTorch: The Geospatial Foundation Models ToolkitCode4
SSL4EO-L: Datasets and Foundation Models for Landsat ImageryCode4
RemoteSAM: Towards Segment Anything for Earth ObservationCode3
BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster responseCode3
PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation ModelsCode3
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation ApplicationsCode3
HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation ModelCode3
SARATR-X: Toward Building A Foundation Model for SAR Target RecognitionCode3
Major TOM: Expandable Datasets for Earth ObservationCode3
SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation ImageryCode3
Video Compression for Spatiotemporal Earth System DataCode2
InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object RecognitionCode2
The Change You Want To Detect: Semantic Change Detection In Earth Observation With Hybrid Data GenerationCode2
Towards a Unified Copernicus Foundation Model for Earth VisionCode2
JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation FrameworkCode2
SARChat-Bench-2M: A Multi-Task Vision-Language Benchmark for SAR Image InterpretationCode2
NUDT4MSTAR: A Large Dataset and Benchmark Towards Remote Sensing Object Recognition in the WildCode2
AnySat: One Earth Observation Model for Many Resolutions, Scales, and ModalitiesCode2
LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language InterpretationCode2
Exploiting Unlabeled Data with Multiple Expert Teachers for Open Vocabulary Aerial Object Detection and Its Orientation AdaptationCode2
Foundation Models for Remote Sensing and Earth Observation: A SurveyCode2
Local Off-Grid Weather Forecasting with Multi-Modal Earth Observation DataCode2
TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation DataCode2
SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing ImageryCode2
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